How Built Environment Affects Travel Behavior: A ComparativeAnalysis of the Connections between Land Use and Vehicle MilesTraveled in U.S. Cities

摘要

Mixed findings have been reported in previous research regarding the impact of builtenvironment on travel behavior, i.e. statistically and practically significant effects found in anumber of empirical studies and insignificant correlations shown in many other studies. It is notclear why the estimated impact is stronger or weaker in certain urban areas, and how effective aproposed land use change/policy will be in changing certain travel behavior. This knowledge gaphas made it difficult for decision makers to evaluate land use plans and policies according totheir impact on vehicle miles traveled (VMT), and consequently their impact on congestionmitigation, energy conservation, and pollution and green house gas emission reduction.This research has several objectives: (1) Re-examine the effects of built-environment factors ontravel behavior, in particular VMT in five U.S. metropolitan areas grouped into four case studyareas; (2) Develop consistent models in all case study areas with the same model specificationand datasets to enable direct comparisons; (3) Identify factors such as existing land usecharacteristics and land use policy decision-making processes that may explain the differentimpacts of built environment on VMT in different urban areas; and (4) Provide a prototype toolfor government agencies and decision-makers to estimate the impact of proposed land usechanges on VMT.The four case study areas include Seattle, WA; Richmond-Petersburg and Norfolk-VirginiaBeach, VA; Baltimore, MD; and Washington DC. Our empirical analysis employs Bayesianmultilevel models with various person-level socio-economic and demographic variables and fivebuilt-environment factors including residential density, employment density, entropy (measuringlevel of mixed-use development), average block size (measuring transit/walking friendliness),and distance to city center (measuring decentralization and level of infill development).Our findings show that promoting compact, mixed-use, small-block and infill developments canbe effective in reducing VMT per person in all four case study areas. However, the effectivenessof land use plans and policies encouraging these types of land developments is different bothacross case study areas and within the same case study area. We have identified several factorsthat potentially influence the connection between built environment shifts and VMT changesincluding urban area size, existing built environment characteristics, transit service coverage andquality, and land use decision-making processes.